OpenDroneMap uses a lot of ideas from computer vision. As a first time contributor, I wish I had known about this book earlier.
Chapters:
2 Image formation
Geometric primitives and transformations • Photometric image formation • The digital camera
3 Image processing
Point operators • Linear filtering • More neighborhood operators • Fourier transforms • Pyramids and wavelets • Geometric transformations • Global optimization
4 Feature detection and matching
Points and patches • Edges • Lines
5 Segmentation
Active contours • Split and merge • Mean shift and mode finding • Normalized cuts • Graph cuts and energy-based methods
6 Feature-based alignment
2D and 3D feature-based alignment • Pose estimation • Geometric intrinsic calibration
7 Structure from motion
Triangulation • Two-frame structure from motion • Factorization • Bundle adjustment • Constrained structure and motion
8 Dense motion estimation
Translational alignment • Parametric motion • Spline-based motion • Optical flow • Layered motion
9 Image stitching
Motion models • Global alignment • Compositing
10 Computational photography
Photometric calibration • High dynamic range imaging • Super-resolution and blur removal • Image matting and compositing • Texture analysis and synthesis
11 Stereo correspondence
Epipolar geometry • Sparse correspondence • Dense correspondence • Local methods • Global optimization • Multi-view stereo
12 3D reconstruction
Shape from X • Active rangefinding • Surface representations • Point-based representations • Volumetric representations • Model-based reconstruction • Recovering texture maps and albedos
13 Image-based rendering
View interpolation • Layered depth images • Light fields and Lumigraphs • Environment mattes • Video-based rendering
14 Recognition
Object detection • Face recognition • Instance recognition • Category recognition • Context and scene understanding • Recognition databases and test sets
Free electronic PDF is available from the author’s website: http://szeliski.org/Book/drafts/SzeliskiBook_20100903_draft.pdf